3 winning teams improve Zestimate accuracy in Zillow competition

Competitors were tasked with increasing the precision of the portal giant's home value estimator

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Dive into the latest Technology affecting RE, July 17, 2018

Competitors in a Zillow competition improved the accuracy of the company's Zestimate, or home value estimator, by 4.4 percent — and will move on to develop a sale price algorithm in the competition's million-dollar second round. The machine learning competition through the data science site Kaggle launched in May 2017 and drew more than 3,800 teams from 91 countries. One-hundred of those teams moved on to the second round and the top three won a total of $50,000 from this round of the competition. Zillow says its Zestimate tool has a rate of error of 4.2 percent in the three counties specified for the competition and tasked competitors with improving that accuracy. Teams worked across Slack, GitHub and Google Drive and ran up costly electric and cloud server bills trying to revamp Zillow's flagship tool over several months. "We've been blown away by the data science community's response to the Zillow Prize. There were lots of innovative solutions and hundreds of teams were a...